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        If you use plots from MultiQC in a publication or presentation, please cite:

        MultiQC: Summarize analysis results for multiple tools and samples in a single report
        Philip Ewels, Måns Magnusson, Sverker Lundin and Max Käller
        Bioinformatics (2016)
        doi: 10.1093/bioinformatics/btw354
        PMID: 27312411

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        About MultiQC

        This report was generated using MultiQC, version 0.9

        You can see a YouTube video describing how to use MultiQC reports here: https://youtu.be/qPbIlO_KWN0

        For more information about MultiQC, including other videos and extensive documentation, please visit http://multiqc.info

        You can report bugs, suggest improvements and find the source code for MultiQC on GitHub: https://github.com/ewels/MultiQC

        MultiQC is published in Bioinformatics:

        MultiQC: Summarize analysis results for multiple tools and samples in a single report
        Philip Ewels, Måns Magnusson, Sverker Lundin and Max Käller
        Bioinformatics (2016)
        doi: 10.1093/bioinformatics/btw354
        PMID: 27312411

        A modular tool to aggregate results from bioinformatics analyses across many samples into a single report.

        Report generated on 2016-12-21, 17:12 based on data in: /Users/philewels/GitHub/MultiQC_website/public_html/examples/wgs/data


        General Statistics

        Showing 6/6 rows and 13/22 columns.
        Sample NameTiTV ratio (novel)TiTV ratio (known)Change rateTs/TvM VariantsAvg. GCInsert Size≥ 30XCoverage% Aligned% Dups% GCM Seqs
        P4107_1001
        1.5
        2.1
        764
        1.995
        4.06
        41%
        358
        74.7%
        36.0
        97.3%
        6.4%
        41%
        383.6
        P4107_1002
        1.5
        2.1
        762
        1.994
        4.07
        41%
        367
        82.3%
        40.0
        97.8%
        9.9%
        41%
        430.2
        P4107_1003
        1.5
        2.1
        761
        1.994
        4.07
        41%
        365
        82.4%
        40.0
        97.6%
        10.5%
        41%
        431.4
        P4107_1004
        1.5
        2.1
        765
        1.996
        4.05
        41%
        363
        84.7%
        46.0
        98.2%
        39.4%
        40%
        498.2
        P4107_1005
        1.5
        2.1
        762
        1.994
        4.07
        41%
        368
        85.3%
        45.0
        98.0%
        24.5%
        41%
        484.2
        P4107_1006
        1.5
        2.1
        761
        1.993
        4.07
        41%
        362
        84.1%
        43.0
        98.1%
        12.4%
        41%
        453.2

        GATK

        GATK is a toolkit offering a wide variety of tools with a primary focus on variant discovery and genotyping.

        Variant Counts

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        Compare Overlap

        Showing 6/6 rows and 5/5 columns.
        Sample NameCompare rateConcordant rateM Evaluated variantsM Known sitesM Novel sites
        P4107_1001
        45.44%
        99.09%
        3.5
        3.4
        1.9
        P4107_1002
        45.75%
        99.09%
        3.5
        3.4
        1.9
        P4107_1003
        44.76%
        99.08%
        3.5
        3.5
        2.0
        P4107_1004
        45.84%
        99.09%
        3.5
        3.4
        1.9
        P4107_1005
        45.82%
        99.10%
        3.5
        3.4
        1.9
        P4107_1006
        45.91%
        99.10%
        3.5
        3.4
        1.9

        SnpEff

        SnpEff is a genetic variant annotation and effect prediction toolbox. It annotates and predicts the effects of variants on genes (such as amino acid changes).

        Variants by Genomic Region

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        Variant Effects by Impact

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        Variant Effects by Class

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        Variant Qualities

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        QualiMap

        QualiMap is a platform-independent application to facilitate the quality control of alignment sequencing data and its derivatives like feature counts.

        Coverage histogram

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        Cumulative coverage genome fraction

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        Insert size histogram

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        GC content distribution

        The dotted line represents a pre-calculated GC destribution for the reference genome.

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        Picard

        Picard is a set of Java command line tools for manipulating high-throughput sequencing data.

        Mark Duplicates

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        FastQ Screen

        FastQ Screen allows you to screen a library of sequences in FastQ format against a set of sequence databases so you can see if the composition of the library matches with what you expect.


        FastQC

        FastQC is a quality control tool for high throughput sequence data, written by Simon Andrews at the Babraham Institute in Cambridge.

        Sequence Quality Histograms

        The mean quality value across each base position in the read. See the FastQC help.

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        Per Sequence Quality Scores

        The number of reads with average quality scores. Shows if a subset of reads has poor quality. See the FastQC help.

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        Per Base Sequence Content

        The proportion of each base position for which each of the four normal DNA bases has been called. See the FastQC help.

        Click a heatmap row to see a line plot for that dataset.

        rollover for sample name
        Position: -
        %T: -
        %C: -
        %A: -
        %G: -

        Per Sequence GC Content

        The average GC content of reads. Normal random library typically have a roughly normal distribution of GC content. See the FastQC help.

        The dashed black line shows theoretical GC content: Human Genome (UCSC hg38).

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        Per Base N Content

        The percentage of base calls at each position for which an N was called. See the FastQC help.

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        Sequence Length Distribution

        All samples have sequences of a single length (151bp).


        Sequence Duplication Levels

        The relative level of duplication found for every sequence. See the FastQC help.

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        Overrepresented sequences

        The total amount of overrepresented sequences found in each library. See the FastQC help for further information.

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        Adapter Content

        The cumulative percentage count of the proportion of your library which has seen each of the adapter sequences at each position. See the FastQC help. Only samples with ≥ 0.1% adapter contamination are shown.

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